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--- |
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license: apache-2.0 |
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language: |
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- ar |
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tags: |
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- SP |
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- Aranizer |
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- Arabic Tokenizer |
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--- |
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# Aranizer | Arabic Tokenizer |
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**Aranizer** is an Arabic SentencePiece-based tokenizer designed for efficient and versatile tokenization. It features a vocabulary size of 32,000 tokens and is optimized for a fertility score of 1.803. The total number of tokens processed is 1,387,929, making it suitable for a wide range of NLP tasks. |
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## Features |
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- **Tokenizer Name**: Aranizer |
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- **Type**: SentencePiece tokenizer |
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- **Vocabulary Size**: 32,000 |
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- **Total Number of Tokens**: 1,387,929 |
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- **Fertility Score**: 1.803 |
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- It supports Arabic Diacritization |
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## Aranizer Collection Achieved State of the Art Arabic Tokenizer |
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The Aranizer tokenizer has achieved state-of-the-art results on the [Arabic Tokenizers Leaderboard](https://huggingface.co/spaces/MohamedRashad/arabic-tokenizers-leaderboard) on Hugging Face. Below is a screenshot highlighting this achievement: |
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<img src="./lb.png" alt="Screenshot showing the Aranizer Tokenizer achieving state of the art" width="800"> |
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## How to Use the Aranizer Tokenizer |
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The Aranizer tokenizer can be easily loaded using the `transformers` library from Hugging Face. Below is an example of how to load and use the tokenizer in your Python project: |
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```python |
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from transformers import AutoTokenizer |
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# Load the Aranizer tokenizer |
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tokenizer = AutoTokenizer.from_pretrained("riotu-lab/Aranizer-SP-32k") |
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# Example usage |
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text = "اكتب النص العربي" |
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tokens = tokenizer.tokenize(text) |
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token_ids = tokenizer.convert_tokens_to_ids(tokens) |
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print("Tokens:", tokens) |
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print("Token IDs:", token_ids) |
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``` |
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```markdown |
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## Citation |
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@article{koubaa2024arabiangpt, |
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title={ArabianGPT: Native Arabic GPT-based Large Language Model}, |
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author={Koubaa, Anis and Ammar, Adel and Ghouti, Lahouari and Necar, Omer and Sibaee, Serry}, |
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year={2024}, |
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publisher={Preprints} |
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} |
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